Digital cameras today are designed to produce usable image files. In order to produce a usable image file, a number of processing steps must occur. These processing steps can occur either on the camera, in which case a finished image file is created (e.g., JPEG), or can be deferred until the image is edited on a computer, in which case a Raw file is created. The finished image file does not require additional processing, so it can be used as soon as it is transferred off of the camera. For this reason, most cameras produce finished images. However, Raw files are becoming more popular with users who demand better image quality.
In both cases the file can be edited on the computer to improve the quality (e.g., exposure, color, sharpness, etc.) and/or to add creative touches (e.g., creative effects such as sepia, addition of borders, addition of text, etc.). However, in the case of the finished image, this processing is necessarily cumulative to the processing already performed on the camera, which can result in lower image quality. In the case of Raw files, no processing has occurred, so the processing can be adjusted from the earliest point. In the current state of the art, this leads to a different user workflow for finished image files than for Raw image files.
Until recently, one of the big advantages that in-camera processing had over computer-based processing was that the Raw sensor data is in a linear color space, i.e., that there exists a linear correlation between the digitized color values and the perceived colors in the image. A linear color space has the advantage that color and exposure corrections are simple to apply and accurate across the entire color space, as more fully described below. This meant that automatic in-camera adjustments could take advantage of the linearity of the color space, whereas all computer-based adjustments had to attempt to reverse engineer the tone-mapping that occurs in the camera. Users, frustrated with this lack of control and consistency, have found a better solution in a relatively new model of image editing-Raw image processing. While it has other advantages beyond the one described hereinabove, for instance, better dynamic range and better suitability as the archival image, one of the biggest advantages of Raw image editing is its easier and more accurate linear image adjustments.
Some higher-end digital cameras available today allow the user to choose to output Raw image data instead of, or in addition to, processed image data (e.g., JPEG). In Raw image processing, the image data is taken directly off of the camera sensor, along with the camera settings, prior to any significant processing being performed by the camera. Thus, Raw image data is unmodified or minimally modified sensor data, typically characterized as linear. The Raw data is subsequently forwarded to a Raw image editing application that produces high-fidelity image edits. Raw image editing applications are fairly easy to use and produce superior results. With Raw image processing, many of the steps utilized with respect to pre-processed image models are skipped, particularly those that take place in the camera itself. Raw image processing is very different than traditional pre-processed image in-camera processing in that the settings and corrections such as exposure, white-point (color) balance, and sharpening are stored with the file and used for processing. None of the processing is done to the stored Raw image itself. The goal of Raw image processing is to save the image data with the minimum amount of processing; indeed to save the digitized sensor data if at all possible.
Raw image editing applications essentially replicate the in-camera processing of pre-processed image editing models. This means that all of the advantages of in-camera processing of pre-processed images (e.g., no degradation due to repeated processing and ability to work in an accurate and easy to manage linear model) are preserved while Raw images are edited and fine-tuned. This closed system is both the strength and weakness of Raw image processing. The ease and quality of the editing for basic adjustments is superb in almost every Raw image editing application available today. However, the design is tightly coupled with the camera design. Each camera model design change drives changes in Raw image processing. Vendors balk at providing full feature support into their editing applications because it's not their core business and because of the complexity of adding in features like combining images, creative input, and preparation for print or press. Many core features, like printing, text, and image composition, are simply not provided.
Composition of images would be extremely problematic with this model anyway. For instance, how would a user compose another image from another camera with this model? Or how would a user combine a post-processed image with a pre-processed one? Basically, Raw image editing applications are generally treated as (yet another) preparation step inserted into the workflow before traditional image editing applications described above. That is, the output of the Raw image editing application is just another input into the traditional image editing application and Raw image processing becomes more work, not less. The quality benefits still accrue, but there is a significantly greater complexity. This, along with the proliferation of non-compatible and redundant Raw image editing models, is a significant impediment to adoption of a Raw image processing model by anyone other than the most dedicated and patient practitioners.
One potential improvement to Raw image processing models to make them less cumbersome to users would be to combine (end-to-end) a Raw image editing application and a traditional image editing application into one application the way that many Raw image processing users do manually today using two separate applications. When users want to adjust color or exposure, they can edit the Raw part of the model and when they want to do traditional pre-processed image editing (e.g., compositing, vector and text editing, printing, and the like) they can use the pre-processed image model with its unified “working or output” color model.
While this may seem a viable approach, it is sub-optimal for a number of reasons. First, it's confusing for users to have to understand when they are working in one model or the other. For instance, how would a user combine images from different cameras or from one camera and a traditional source like a JPEG? Or how would a user leverage the expertise of a camera manufacturer's Raw image processing model and a software vendor's pre-processed image editing and creative tools in one application? Pasting the two models together does not address these issues.
Perhaps the biggest barrier to unifying the pre-processed and Raw image processing models, however, is that while the workflows appear to be similar-they both have exposure and color correction steps, for example-the tools and underlying technology are actually completely different. Each of them produces different results using different processing algorithms. In fact, Raw image processing corrections often don't look the same as edits made in a processed image editing application.
Accordingly, a method for unifying image editing for both Raw and pre-processed images would be desirable. Additionally, a method for merging the disparate image processing models of Raw and pre-processed image editing into a largely unified design that can deal interchangeably with Raw and pre-processed or linear data using common tools and workflow would be advantageous.